Correlation Between PP Presisi and Acset Indonusa
Can any of the company-specific risk be diversified away by investing in both PP Presisi and Acset Indonusa at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining PP Presisi and Acset Indonusa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PP Presisi Tbk and Acset Indonusa Tbk, you can compare the effects of market volatilities on PP Presisi and Acset Indonusa and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in PP Presisi with a short position of Acset Indonusa. Check out your portfolio center. Please also check ongoing floating volatility patterns of PP Presisi and Acset Indonusa.
Diversification Opportunities for PP Presisi and Acset Indonusa
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between PPRE and Acset is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding PP Presisi Tbk and Acset Indonusa Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Acset Indonusa Tbk and PP Presisi is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on PP Presisi Tbk are associated (or correlated) with Acset Indonusa. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Acset Indonusa Tbk has no effect on the direction of PP Presisi i.e., PP Presisi and Acset Indonusa go up and down completely randomly.
Pair Corralation between PP Presisi and Acset Indonusa
Assuming the 90 days trading horizon PP Presisi Tbk is expected to under-perform the Acset Indonusa. In addition to that, PP Presisi is 1.28 times more volatile than Acset Indonusa Tbk. It trades about -0.21 of its total potential returns per unit of risk. Acset Indonusa Tbk is currently generating about 0.01 per unit of volatility. If you would invest 8,900 in Acset Indonusa Tbk on November 3, 2024 and sell it today you would earn a total of 0.00 from holding Acset Indonusa Tbk or generate 0.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.0% |
| Values | Daily Returns |
PP Presisi Tbk vs. Acset Indonusa Tbk
Performance |
| Timeline |
| PP Presisi Tbk |
| Acset Indonusa Tbk |
PP Presisi and Acset Indonusa Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with PP Presisi and Acset Indonusa
The main advantage of trading using opposite PP Presisi and Acset Indonusa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PP Presisi position performs unexpectedly, Acset Indonusa can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Acset Indonusa will offset losses from the drop in Acset Indonusa's long position.| PP Presisi vs. Wijaya Karya Bangunan | PP Presisi vs. PP Properti Tbk | PP Presisi vs. Wijaya Karya Beton | PP Presisi vs. Soechi Lines Tbk |
| Acset Indonusa vs. Bekasi Fajar Industrial | Acset Indonusa vs. Nusa Raya Cipta | Acset Indonusa vs. Wijaya Karya Beton | Acset Indonusa vs. Agung Podomoro Land |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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